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      Activated PTHLH Coupling Feedback Phosphoinositide to G-Protein Receptor Signal-Induced Cell Adhesion Network in Human Hepatocellular Carcinoma by Systems-Theoretic Analysis

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          Abstract

          Studies were done on analysis of biological processes in the same high expression (fold change ≥2) activated PTHLH feedback-mediated cell adhesion gene ontology (GO) network of human hepatocellular carcinoma (HCC) compared with the corresponding low expression activated GO network of no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection). Activated PTHLH feedback-mediated cell adhesion network consisted of anaphase-promoting complex-dependent proteasomal ubiquitin-dependent protein catabolism, cell adhesion, cell differentiation, cell-cell signaling, G-protein-coupled receptor protein signaling pathway, intracellular transport, metabolism, phosphoinositide-mediated signaling, positive regulation of transcription, regulation of cyclin-dependent protein kinase activity, regulation of transcription, signal transduction, transcription, and transport in HCC. We proposed activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network. Our hypothesis was verified by the different activated PTHLH feedback-mediated cell adhesion GO network of HCC compared with the corresponding inhibited GO network of no-tumor hepatitis/cirrhotic tissues, or the same compared with the corresponding inhibited GO network of HCC. Activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network included BUB1B, GNG10, PTHR2, GNAZ, RFC4, UBE2C, NRXN3, BAP1, PVRL2, TROAP, and VCAN in HCC from GEO dataset using gene regulatory network inference method and our programming.

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          Most cited references30

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          Gene expression in fixed tissues and outcome in hepatocellular carcinoma.

          It is a challenge to identify patients who, after undergoing potentially curative treatment for hepatocellular carcinoma, are at greatest risk for recurrence. Such high-risk patients could receive novel interventional measures. An obstacle to the development of genome-based predictors of outcome in patients with hepatocellular carcinoma has been the lack of a means to carry out genomewide expression profiling of fixed, as opposed to frozen, tissue. We aimed to demonstrate the feasibility of gene-expression profiling of more than 6000 human genes in formalin-fixed, paraffin-embedded tissues. We applied the method to tissues from 307 patients with hepatocellular carcinoma, from four series of patients, to discover and validate a gene-expression signature associated with survival. The expression-profiling method for formalin-fixed, paraffin-embedded tissue was highly effective: samples from 90% of the patients yielded data of high quality, including samples that had been archived for more than 24 years. Gene-expression profiles of tumor tissue failed to yield a significant association with survival. In contrast, profiles of the surrounding nontumoral liver tissue were highly correlated with survival in a training set of tissue samples from 82 Japanese patients, and the signature was validated in tissues from an independent group of 225 patients from the United States and Europe (P=0.04). We have demonstrated the feasibility of genomewide expression profiling of formalin-fixed, paraffin-embedded tissues and have shown that a reproducible gene-expression signature correlated with survival is present in liver tissue adjacent to the tumor in patients with hepatocellular carcinoma. Copyright 2008 Massachusetts Medical Society.
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            Inferring gene regulatory networks from multiple microarray datasets.

            Microarray gene expression data has increasingly become the common data source that can provide insights into biological processes at a system-wide level. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to a large number of genes, which makes the problem of inferring gene regulatory network an ill-posed one. On the other hand, gene expression data generated by different groups worldwide are increasingly accumulated on many species and can be accessed from public databases or individual websites, although each experiment has only a limited number of time-points. This paper proposes a novel method to combine multiple time-course microarray datasets from different conditions for inferring gene regulatory networks. The proposed method is called GNR (Gene Network Reconstruction tool) which is based on linear programming and a decomposition procedure. The method theoretically ensures the derivation of the most consistent network structure with respect to all of the datasets, thereby not only significantly alleviating the problem of data scarcity but also remarkably improving the prediction reliability. We tested GNR using both simulated data and experimental data in yeast and Arabidopsis. The result demonstrates the effectiveness of GNR in terms of predicting new gene regulatory relationship in yeast and Arabidopsis. The software is available from http://zhangorup.aporc.org/bioinfo/grninfer/, http://digbio.missouri.edu/grninfer/ and http://intelligent.eic.osaka-sandai.ac.jp or upon request from the authors.
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              Stromal cell-derived factor-1alpha stimulates tyrosine phosphorylation of multiple focal adhesion proteins and induces migration of hematopoietic progenitor cells: roles of phosphoinositide-3 kinase and protein kinase C.

              The stromal cell-derived factor-1 (SDF-1) is an alpha chemokine that binds to the CXCR4 receptor. Knock-out studies in mice demonstrate that this ligand-receptor pair is essential in hematopoiesis. One function of SDF-1 appears to be the regulation of migration of hematopoietic progenitor cells. We previously characterized signal transduction pathways induced by SDF-1alpha in human hematopoietic progenitors and found tyrosine phosphorylation of focal adhesion components, including the related adhesion focal tyrosine kinase (RAFTK), the adaptor molecule p130 Cas, and the cytoskeletal protein paxillin. To better understand the functional role of signaling molecules connecting the CXCR4 receptor to the process of hematopoietic migration, we studied SDF-1alpha-mediated pathways in a model hematopoietic progenitor cell line (CTS), as well as in primary human bone marrow CD34(+) cells. We observed that several other focal adhesion components, including focal adhesion kinase (FAK) and the adaptor molecules Crk and Crk-L, are phosphorylated on SDF-1alpha stimulation. Using a series of specific small molecule inhibitors, both protein kinase C (PKC) and phosphoinositide-3 kinase (PI-3K) appeared to be required for SDF-1alpha-mediated phosphorylation of focal adhesion proteins and the migration of both CTS and primary marrow CD34(+) cells, whereas the mitogen-activated protein kinases ERK-1 and -2 were not. These studies further delineate the molecular pathways mediating hematopoietic progenitor migration and response to an essential chemokine, SDF-1alpha. (Blood. 2000;95:2505-2513)
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                Author and article information

                Journal
                ScientificWorldJournal
                ScientificWorldJournal
                TSWJ
                The Scientific World Journal
                The Scientific World Journal
                1537-744X
                2012
                10 September 2012
                : 2012
                : 428979
                Affiliations
                1Biomedical Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
                2Lab of Computational Linguistics, School of Humanities and Social Sciences, Tsinghua University, Beijing 100084, China
                Author notes

                Academic Editors: S. Guleria and S. Yasmin

                Article
                10.1100/2012/428979
                3444843
                22997493
                f302b896-9bd0-46bd-9d6e-02211c47dd43
                Copyright © 2012 Lin Wang et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 June 2012
                : 29 July 2012
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